{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0_PRh4VkNYOs"
   },
   "source": [
    "# 了解RAG 中的 Embedding Vectors\n",
    "\n",
    "1. 什么是`embedding`\n",
    "2. Sentence BERT\n",
    "3. 如何选取`embedding model`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S5vWsPi-NYOt"
   },
   "source": [
    "## 什么是`embedding`\n",
    "\n",
    "考虑一下如何表示“男人” ， “女人”，我们可以从性别上出发，假设男性性别可以表示‘1’ ， 女性性别可以表示为‘9’，即可将“男人” ， “女人”区分开来\n",
    "\n",
    "那么当加入“男孩” ，“女孩”的时候，单纯靠性别已经无法完全区分上述四个单词，此时可以引入年龄， **\"男人\"：[1,35] , \"女人\":[9,35] , \"男孩\"：[1,10] , \"女孩\":[9,10]**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "6XIAD9kVNYOu",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190178055,
     "user_tz": -60,
     "elapsed": 1805,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "8c22f9af-3247-4303-c6af-357018bf8191"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
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      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 40836 (\\N{CJK UNIFIED IDEOGRAPH-9F84}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24615 (\\N{CJK UNIFIED IDEOGRAPH-6027}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21035 (\\N{CJK UNIFIED IDEOGRAPH-522B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30007 (\\N{CJK UNIFIED IDEOGRAPH-7537}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20154 (\\N{CJK UNIFIED IDEOGRAPH-4EBA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22899 (\\N{CJK UNIFIED IDEOGRAPH-5973}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23401 (\\N{CJK UNIFIED IDEOGRAPH-5B69}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.rcParams['font.sans-serif'] = ['Kaitt', 'SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 定义点的坐标和标签\n",
    "points = {\n",
    "    \"男人\": [1, 35],\n",
    "    \"女人\": [9, 35],\n",
    "    \"男孩\": [1, 10],\n",
    "    \"女孩\": [9, 10]\n",
    "}\n",
    "\n",
    "x_values = [point[0] for point in points.values()]\n",
    "y_values = [point[1] for point in points.values()]\n",
    "labels = list(points.keys())\n",
    "\n",
    "plt.figure(figsize=(12, 8))\n",
    "for i, label in enumerate(labels):\n",
    "    plt.scatter(x_values[i], y_values[i], label=label)\n",
    "\n",
    "# 设置X轴和Y轴的范围和精度\n",
    "plt.xlim([0,10])\n",
    "plt.ylim([0,50])\n",
    "plt.xticks(np.arange(0, 10, 1))\n",
    "plt.yticks(np.arange(0, 50, 10))\n",
    "\n",
    "# 添加标签\n",
    "for i, label in enumerate(labels):\n",
    "    plt.annotate(label, (x_values[i], y_values[i]), textcoords=\"offset points\", xytext=(0,10), ha='center')\n",
    "# 设置图表标题和坐标轴标签\n",
    "plt.title(\"embedding\")\n",
    "plt.xlabel(\"性别\")\n",
    "plt.ylabel(\"年龄\")\n",
    "# 显示图例\n",
    "plt.legend()\n",
    "# 显示图表\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zsFxf9mmNYOu"
   },
   "source": [
    "随着词汇的逐渐增加，二维已经不足以区分单词，例如引入新的单词 “国王” ，“皇后”,只靠年龄和性别，已经无法区分国王 —— 男人 ， 皇后———女人\n",
    "\n",
    "所以我们引入新的特征，例如'皇室的' ，则 **\"男人\": [1, 35, 1], \"女人\": [9, 35, 1],\"男孩\": [1, 10, 1],\"女孩\": [9, 10, 1],\"国王\": [1, 35, 9],\"皇后\": [9, 35, 9]**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "uf3LZR7KNYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190180146,
     "user_tz": -60,
     "elapsed": 2095,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "ba24a5dc-9f1c-4d9f-b4ef-14b494a887dd"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30343 (\\N{CJK UNIFIED IDEOGRAPH-7687}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23460 (\\N{CJK UNIFIED IDEOGRAPH-5BA4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22269 (\\N{CJK UNIFIED IDEOGRAPH-56FD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29579 (\\N{CJK UNIFIED IDEOGRAPH-738B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21518 (\\N{CJK UNIFIED IDEOGRAPH-540E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "points = {\n",
    "    \"男人\": [1, 35, 1],\n",
    "    \"女人\": [9, 35, 1],\n",
    "    \"男孩\": [1, 10, 1],\n",
    "    \"女孩\": [9, 10, 1],\n",
    "    \"国王\": [1, 35, 9],\n",
    "    \"皇后\": [9, 35, 9]\n",
    "}\n",
    "\n",
    "x_coords = [point[0] for point in points.values()]\n",
    "y_coords = [point[1] for point in points.values()]\n",
    "z_coords = [point[2] for point in points.values()]\n",
    "labels = list(points.keys())\n",
    "\n",
    "# 创建图形和三维坐标轴\n",
    "fig = plt.figure(figsize=(12, 10))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "for i, label in enumerate(labels):\n",
    "    ax.scatter(x_coords[i], y_coords[i], z_coords[i], label=label , s=50)\n",
    "\n",
    "# 为每个点添加标签，并设置偏移量\n",
    "for i, label in enumerate(labels):\n",
    "    ax.text(x_coords[i], y_coords[i], z_coords[i], label, fontsize=15, horizontalalignment='left', verticalalignment='bottom')\n",
    "\n",
    "\n",
    "# 设置标签\n",
    "ax.set_xlabel('性别')\n",
    "ax.set_ylabel('年龄')\n",
    "ax.set_zlabel('皇室')\n",
    "\n",
    "# 调整视角\n",
    "ax.view_init(elev=25., azim= -15)\n",
    "# 显示图形\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h1am0pMnNYOv"
   },
   "source": [
    "# embedding模型选取"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JdIsP35GNYOv"
   },
   "source": [
    "## m3e模型"
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "!pip install sentence-transformers\n"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "H1U5VazAOxRx",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190280842,
     "user_tz": -60,
     "elapsed": 100700,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "2eb1424e-1521-4ffe-b10f-6124141eae4e"
   },
   "execution_count": 3,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Collecting sentence-transformers\n",
      "  Downloading sentence_transformers-2.7.0-py3-none-any.whl (171 kB)\n",
      "\u001B[2K     \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m171.5/171.5 kB\u001B[0m \u001B[31m2.9 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\n",
      "\u001B[?25hRequirement already satisfied: transformers<5.0.0,>=4.34.0 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (4.40.1)\n",
      "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (4.66.4)\n",
      "Requirement already satisfied: torch>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (2.2.1+cu121)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (1.25.2)\n",
      "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (1.2.2)\n",
      "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (1.11.4)\n",
      "Requirement already satisfied: huggingface-hub>=0.15.1 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (0.20.3)\n",
      "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (9.4.0)\n",
      "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (3.14.0)\n",
      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (2023.6.0)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (2.31.0)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (6.0.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (4.11.0)\n",
      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers) (24.0)\n",
      "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers) (1.12)\n",
      "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers) (3.3)\n",
      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers) (3.1.3)\n",
      "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.11.0->sentence-transformers)\n",
      "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
      "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.11.0->sentence-transformers)\n",
      "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
      "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.11.0->sentence-transformers)\n",
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      "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, sentence-transformers\n",
      "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105 sentence-transformers-2.7.0\n"
     ]
    }
   ]
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    "id": "Kqu7twt-NYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190308649,
     "user_tz": -60,
     "elapsed": 27813,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "c8361891-0b7d-4c18-a2f3-29066e9f3ab4"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
      "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
      "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
      "You will be able to reuse this secret in all of your notebooks.\n",
      "Please note that authentication is recommended but still optional to access public models or datasets.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
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     "metadata": {}
    },
    {
     "output_type": "display_data",
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      ],
      "application/vnd.jupyter.widget-view+json": {
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     "metadata": {}
    },
    {
     "output_type": "display_data",
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      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
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     "metadata": {}
    },
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     "metadata": {}
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    {
     "output_type": "display_data",
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      ],
      "application/vnd.jupyter.widget-view+json": {
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     "metadata": {}
    },
    {
     "output_type": "display_data",
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      ],
      "application/vnd.jupyter.widget-view+json": {
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     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
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      ],
      "application/vnd.jupyter.widget-view+json": {
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     "metadata": {}
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      ],
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       "version_major": 2,
       "version_minor": 0,
       "model_id": "f8119b87d1fc4db3830377aeada7e784"
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     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
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      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "111354ab05524b3c97bb241ca4afef44"
      }
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
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      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "ad8f1caab8f948bdb1e496b27508d4ea"
      }
     },
     "metadata": {}
    }
   ],
   "source": [
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "model = SentenceTransformer('moka-ai/m3e-base')\n",
    "\n",
    "#Our sentences we like to encode\n",
    "sentences =['为什么良好的睡眠对健康至关重要?' ,\n",
    "        '良好的睡眠有助于身体修复自身,增强免疫系统',\n",
    "        '在监督学习中，算法经常需要大量的标记数据来进行有效学习',\n",
    "        '睡眠不足可能导致长期健康问题,如心脏病和糖尿病',\n",
    "        '这种学习方法依赖于数据质量和数量',\n",
    "        '它帮助维持正常的新陈代谢和体重控制',\n",
    "        '睡眠对儿童和青少年的大脑发育和成长尤为重要',\n",
    "        '良好的睡眠有助于提高日间的工作效率和注意力',\n",
    "        '监督学习的成功取决于特征选择和算法的选择',\n",
    "        '量子计算机的发展仍处于早期阶段，面临技术和物理挑战',\n",
    "        '量子计算机与传统计算机不同，后者使用二进制位进行计算',\n",
    "        '机器学习使我睡不着觉',\n",
    "]\n",
    "#Sentences are encoded by calling model.encode()\n",
    "embeddings = model.encode(sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HVJwJ2wCNYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190308649,
     "user_tz": -60,
     "elapsed": 4,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "362921cc-6041-4233-8ae4-1e8d45afb5e7"
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "source": [
    "len(embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "AuJDb80hNYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190308649,
     "user_tz": -60,
     "elapsed": 3,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "1ee4a55d-4d5c-456a-c4aa-0fd0f18e650a"
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "768"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "len(embeddings[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "NuzELm8ZNYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190309249,
     "user_tz": -60,
     "elapsed": 602,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "import numpy as np\n",
    "\n",
    "tsne = TSNE(n_components=2 ,  perplexity=5)\n",
    "embeddings_2d = tsne.fit_transform(embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "yH3h5wedNYOv",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190310302,
     "user_tz": -60,
     "elapsed": 1056,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "8aee07d4-5351-46fb-cbe3-ecf342696718"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20026 (\\N{CJK UNIFIED IDEOGRAPH-4E3A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20160 (\\N{CJK UNIFIED IDEOGRAPH-4EC0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20040 (\\N{CJK UNIFIED IDEOGRAPH-4E48}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33391 (\\N{CJK UNIFIED IDEOGRAPH-826F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22909 (\\N{CJK UNIFIED IDEOGRAPH-597D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30340 (\\N{CJK UNIFIED IDEOGRAPH-7684}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30561 (\\N{CJK UNIFIED IDEOGRAPH-7761}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30496 (\\N{CJK UNIFIED IDEOGRAPH-7720}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23545 (\\N{CJK UNIFIED IDEOGRAPH-5BF9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20581 (\\N{CJK UNIFIED IDEOGRAPH-5065}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24247 (\\N{CJK UNIFIED IDEOGRAPH-5EB7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33267 (\\N{CJK UNIFIED IDEOGRAPH-81F3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20851 (\\N{CJK UNIFIED IDEOGRAPH-5173}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26377 (\\N{CJK UNIFIED IDEOGRAPH-6709}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21161 (\\N{CJK UNIFIED IDEOGRAPH-52A9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20110 (\\N{CJK UNIFIED IDEOGRAPH-4E8E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36523 (\\N{CJK UNIFIED IDEOGRAPH-8EAB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20307 (\\N{CJK UNIFIED IDEOGRAPH-4F53}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20462 (\\N{CJK UNIFIED IDEOGRAPH-4FEE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22797 (\\N{CJK UNIFIED IDEOGRAPH-590D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33258 (\\N{CJK UNIFIED IDEOGRAPH-81EA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22686 (\\N{CJK UNIFIED IDEOGRAPH-589E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24378 (\\N{CJK UNIFIED IDEOGRAPH-5F3A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20813 (\\N{CJK UNIFIED IDEOGRAPH-514D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30123 (\\N{CJK UNIFIED IDEOGRAPH-75AB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31995 (\\N{CJK UNIFIED IDEOGRAPH-7CFB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32479 (\\N{CJK UNIFIED IDEOGRAPH-7EDF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22312 (\\N{CJK UNIFIED IDEOGRAPH-5728}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30417 (\\N{CJK UNIFIED IDEOGRAPH-76D1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30563 (\\N{CJK UNIFIED IDEOGRAPH-7763}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23398 (\\N{CJK UNIFIED IDEOGRAPH-5B66}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20064 (\\N{CJK UNIFIED IDEOGRAPH-4E60}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20013 (\\N{CJK UNIFIED IDEOGRAPH-4E2D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 65292 (\\N{FULLWIDTH COMMA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31639 (\\N{CJK UNIFIED IDEOGRAPH-7B97}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27861 (\\N{CJK UNIFIED IDEOGRAPH-6CD5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32463 (\\N{CJK UNIFIED IDEOGRAPH-7ECF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24120 (\\N{CJK UNIFIED IDEOGRAPH-5E38}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38656 (\\N{CJK UNIFIED IDEOGRAPH-9700}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22823 (\\N{CJK UNIFIED IDEOGRAPH-5927}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 37327 (\\N{CJK UNIFIED IDEOGRAPH-91CF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26631 (\\N{CJK UNIFIED IDEOGRAPH-6807}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35760 (\\N{CJK UNIFIED IDEOGRAPH-8BB0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25968 (\\N{CJK UNIFIED IDEOGRAPH-6570}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25454 (\\N{CJK UNIFIED IDEOGRAPH-636E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26469 (\\N{CJK UNIFIED IDEOGRAPH-6765}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36827 (\\N{CJK UNIFIED IDEOGRAPH-8FDB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 34892 (\\N{CJK UNIFIED IDEOGRAPH-884C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25928 (\\N{CJK UNIFIED IDEOGRAPH-6548}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36275 (\\N{CJK UNIFIED IDEOGRAPH-8DB3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21487 (\\N{CJK UNIFIED IDEOGRAPH-53EF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33021 (\\N{CJK UNIFIED IDEOGRAPH-80FD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23548 (\\N{CJK UNIFIED IDEOGRAPH-5BFC}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33268 (\\N{CJK UNIFIED IDEOGRAPH-81F4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38271 (\\N{CJK UNIFIED IDEOGRAPH-957F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26399 (\\N{CJK UNIFIED IDEOGRAPH-671F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38382 (\\N{CJK UNIFIED IDEOGRAPH-95EE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 39064 (\\N{CJK UNIFIED IDEOGRAPH-9898}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22914 (\\N{CJK UNIFIED IDEOGRAPH-5982}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24515 (\\N{CJK UNIFIED IDEOGRAPH-5FC3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33039 (\\N{CJK UNIFIED IDEOGRAPH-810F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30149 (\\N{CJK UNIFIED IDEOGRAPH-75C5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21644 (\\N{CJK UNIFIED IDEOGRAPH-548C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31958 (\\N{CJK UNIFIED IDEOGRAPH-7CD6}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23615 (\\N{CJK UNIFIED IDEOGRAPH-5C3F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36825 (\\N{CJK UNIFIED IDEOGRAPH-8FD9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31181 (\\N{CJK UNIFIED IDEOGRAPH-79CD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26041 (\\N{CJK UNIFIED IDEOGRAPH-65B9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20381 (\\N{CJK UNIFIED IDEOGRAPH-4F9D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36182 (\\N{CJK UNIFIED IDEOGRAPH-8D56}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36136 (\\N{CJK UNIFIED IDEOGRAPH-8D28}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23427 (\\N{CJK UNIFIED IDEOGRAPH-5B83}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24110 (\\N{CJK UNIFIED IDEOGRAPH-5E2E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32500 (\\N{CJK UNIFIED IDEOGRAPH-7EF4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25345 (\\N{CJK UNIFIED IDEOGRAPH-6301}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27491 (\\N{CJK UNIFIED IDEOGRAPH-6B63}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26032 (\\N{CJK UNIFIED IDEOGRAPH-65B0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38472 (\\N{CJK UNIFIED IDEOGRAPH-9648}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20195 (\\N{CJK UNIFIED IDEOGRAPH-4EE3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35874 (\\N{CJK UNIFIED IDEOGRAPH-8C22}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25511 (\\N{CJK UNIFIED IDEOGRAPH-63A7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21046 (\\N{CJK UNIFIED IDEOGRAPH-5236}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20799 (\\N{CJK UNIFIED IDEOGRAPH-513F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31461 (\\N{CJK UNIFIED IDEOGRAPH-7AE5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38738 (\\N{CJK UNIFIED IDEOGRAPH-9752}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23569 (\\N{CJK UNIFIED IDEOGRAPH-5C11}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33041 (\\N{CJK UNIFIED IDEOGRAPH-8111}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21457 (\\N{CJK UNIFIED IDEOGRAPH-53D1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32946 (\\N{CJK UNIFIED IDEOGRAPH-80B2}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25104 (\\N{CJK UNIFIED IDEOGRAPH-6210}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23588 (\\N{CJK UNIFIED IDEOGRAPH-5C24}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25552 (\\N{CJK UNIFIED IDEOGRAPH-63D0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 39640 (\\N{CJK UNIFIED IDEOGRAPH-9AD8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26085 (\\N{CJK UNIFIED IDEOGRAPH-65E5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38388 (\\N{CJK UNIFIED IDEOGRAPH-95F4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24037 (\\N{CJK UNIFIED IDEOGRAPH-5DE5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20316 (\\N{CJK UNIFIED IDEOGRAPH-4F5C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29575 (\\N{CJK UNIFIED IDEOGRAPH-7387}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27880 (\\N{CJK UNIFIED IDEOGRAPH-6CE8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24847 (\\N{CJK UNIFIED IDEOGRAPH-610F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21147 (\\N{CJK UNIFIED IDEOGRAPH-529B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21151 (\\N{CJK UNIFIED IDEOGRAPH-529F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21462 (\\N{CJK UNIFIED IDEOGRAPH-53D6}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20915 (\\N{CJK UNIFIED IDEOGRAPH-51B3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29305 (\\N{CJK UNIFIED IDEOGRAPH-7279}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24449 (\\N{CJK UNIFIED IDEOGRAPH-5F81}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36873 (\\N{CJK UNIFIED IDEOGRAPH-9009}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25321 (\\N{CJK UNIFIED IDEOGRAPH-62E9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23376 (\\N{CJK UNIFIED IDEOGRAPH-5B50}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35745 (\\N{CJK UNIFIED IDEOGRAPH-8BA1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26426 (\\N{CJK UNIFIED IDEOGRAPH-673A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23637 (\\N{CJK UNIFIED IDEOGRAPH-5C55}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20173 (\\N{CJK UNIFIED IDEOGRAPH-4ECD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22788 (\\N{CJK UNIFIED IDEOGRAPH-5904}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26089 (\\N{CJK UNIFIED IDEOGRAPH-65E9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38454 (\\N{CJK UNIFIED IDEOGRAPH-9636}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27573 (\\N{CJK UNIFIED IDEOGRAPH-6BB5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38754 (\\N{CJK UNIFIED IDEOGRAPH-9762}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20020 (\\N{CJK UNIFIED IDEOGRAPH-4E34}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25216 (\\N{CJK UNIFIED IDEOGRAPH-6280}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26415 (\\N{CJK UNIFIED IDEOGRAPH-672F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29289 (\\N{CJK UNIFIED IDEOGRAPH-7269}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29702 (\\N{CJK UNIFIED IDEOGRAPH-7406}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25361 (\\N{CJK UNIFIED IDEOGRAPH-6311}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25112 (\\N{CJK UNIFIED IDEOGRAPH-6218}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 19982 (\\N{CJK UNIFIED IDEOGRAPH-4E0E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20256 (\\N{CJK UNIFIED IDEOGRAPH-4F20}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21516 (\\N{CJK UNIFIED IDEOGRAPH-540C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21518 (\\N{CJK UNIFIED IDEOGRAPH-540E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32773 (\\N{CJK UNIFIED IDEOGRAPH-8005}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20351 (\\N{CJK UNIFIED IDEOGRAPH-4F7F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29992 (\\N{CJK UNIFIED IDEOGRAPH-7528}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20108 (\\N{CJK UNIFIED IDEOGRAPH-4E8C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20301 (\\N{CJK UNIFIED IDEOGRAPH-4F4D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22120 (\\N{CJK UNIFIED IDEOGRAPH-5668}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25105 (\\N{CJK UNIFIED IDEOGRAPH-6211}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30528 (\\N{CJK UNIFIED IDEOGRAPH-7740}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35273 (\\N{CJK UNIFIED IDEOGRAPH-89C9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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am5qatGXLFpWWlmr16tUKCQlxa29vb1d2drZycnI0adIkhYeHe+zDZrOprKxMixcvVklJiccdvZaWFq1fv16Seu2HvLw8paSk0Bf0xWn3hc1m82jrzZAhQ/T73/9er7zyin7961/riy++UHh4uG677Tbde++9GjNmzGntDwAGI8Izzpnm5mZlZWUpNzfXbXl1dbVWrFghi8Wi8vJyj+0yMjJkGIaOHTum/Px8ZWRkuLUXFBSooaHBNT6zoKDAYx+pqamSpJqaGq/HsNvtcjqdamho0LJly2S3293ai4uLVVRUJMMwFB8fr+Li4h6PcfjwYW3evNnjyyVyc3PV3NwsSb32gyT6gr44o744E0FBQfrRj36kH/3oR2e0PQAMdgzbAAAAAEwiPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkZttAn2pvb9fWrVtVU1Oj/fv3q7Oz098lAQAA9BnCM/rMK6+8opycHB06dMi1bNiwYZo4caKysrL8WBkAAEDfIDyjT7z22mu67bbbPJYfP35ct956qywWi374wx/6oTIAAIC+w5hnnLWOjg7df//9va7zwAMPqKOjw0cVAQAAnBuEZ5y1kpIS1dTU9LrO/v37tX37dh9VBAAAcG4wbANn7eDBg6bWW7BggUaMGCFJyszMVF1dnaZOnep1XavVqvj4eC1dutRr+8qVKxUWFqaKigqv+0hOTpYkJSUl9XiMsLAwxcTEaM2aNcrPz/dot9vtslqtamxs9LqP6OhoSVJiYqLmzZvn9RiZmZmSpMLCQhUWFvbYHhUVRV/QFx7tp+oLAIDvWQzDMPxdRF9wOByKjIxUfX29IiIi/F3OoLJ9+3alp6ebWm/GjBk+qAgAECi4fiPQcOsCZ2369OkaO3asLBaL13aLxaJx48bp29/+to8rAwAA6FuEZ5w1q9Xq+vP2yQG6+/m6dev4MzMAAAh4pBn0iRtuuEGbN2/W+PHj3ZaPHz9eb731lm644QY/VQYAANB3GPOMPmUYhkpLS1VTU6O4uDilpKT0OJwDAACu3wg0zLaBPmWxWJSWlubvMgAAAM4Jhm0AAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAAAAYBLhGQAAADCJ8AwAAACYRHgGAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCTCMwAAAGAS4RkAAAAwifAMAAAAmER4BgAAAEwiPAMAAAAmBfu7AAAAfKakRFq0SAoNdV/e2Smlp0s7d0qtrZ7bNTZKlZXS2rXShg1S8EmXz7Y2adUqKTVVmjNHGjrUcx8JCdKmTdLcuVJVlWd7U5O0ZYtUWiqtXi2FhLi3t7dL2dlSTo40aZIUHu65D5tNKiuTFi/uOlfrSffIWlqk9eu7/ru3fsjLk1JSfNIXw776Sp9JGjZ9+j/q7cu++NvfpIcflrZulRwOKS1NevZZafx4z20AEwjPAIDBo7lZysqScnPdl1dXSytWSBaLVF7uuV1GhmQY0rFjUn5+1/MTFRRIDQ2S0ylNm9b1/GSpqV3/1tR4P4bd3rV9Q4O0bFnX8xMVF0tFRV11xMd3Pe/pGIcPS5s3S+PGubfn5nb1gdR7P0g+64vjH3ygKyMjVf/BB4qIiOha3pd98ckn0oUXSoWFUlCQdPfd0oIF0rZtntsAJhCeAQDAwHXLLV2PE5//+tf+qwcBjzHPAABgcNi3T3r6aeknP/F3JQhghGcAADDwff21NH269P3vSytX+rsaBDDCMwAAGPgee0waPVpat87flSDA+SQ85+bmymKxuD0mTJjgam9padG9996r888/X+Hh4brlllt08OBBX5QGAAAGgwMHpEsu6fogJHAWfPaBwUmTJum99977x4FPmNrm/vvv19tvv62NGzcqMjJS9913n26++WZ9+OGHvioPADAQdXR0zTrxf/9v1/RwwcFdU5Q1N0thYf6uLiCUlJRo0aJFCu2e1m7PHiklRZ01NUr/f/9PO5cvV+uJU9odPSoZhhofe0yVV1+ttY8/rg0bNrhd9/Xll2qbOFGr2to06X//V5I0ffp0Wbunqtu7VyorU4LNpk05OZo7d66qTpzer7FRamhQ0+9+py0jRqj0pZe0evVqhZw4pd2XX6r9ssuUnZ2tnJwcTfr0U4UPGyZdcYXb+dlsNpWVlWnx4sUqKSn5Rw3faGlp0fpvpvdz64dvdHZ2Kj09XXl5eUpJSXHvC1e5jaqsrNTatWs9+0JSW1ubVq1apdTUVM2ZM0dDvUzvl5CQoE2bNnn2xTeampq0ZcsWlZaWevaFpPb2dmVnZ2v58uUe2w6Wc8/JydGkSZMU7mVqw+7XgRk+C8/BwcGKjY31WF5fX6/nn39eL7/8sq699lpJ0osvvqikpCSVlpYqtXuqGQAATkdra9f41qKirinKOjq67jpWVEjf+lbXVGUjR/q7yn6vublZWVlZyu2e1i4jQyoqUvX992vF7t2yWCwqP3FKu4ICqaVFGS+8IEPSsWPHlJ+fr4wTp7RLTVXBXXep4ec/V3t7uyTpg5OnqluxQqlz5kiSampq3I/xzVR19v375dy9Ww0NDVq2bJnsJ05pl5qq4l/+UkVFRTIMQ/GtrSq+7bau4Rs6cbWunHH48GFt3rxZ406a3i83N1fN30zv59YP36iurtaKb6b38+gLdXdZhgzD8N4XkgoKCtTQ0CCn06lp06apwMv0ft11evTFN+x2u5xOp/e+kFRcXKyioiKP7QbTuRuGofj4eBV7mdrwdPKmz8Y8f/nll4qLi9P48eM1f/587d27V5K0a9cuOZ1OzZw507XuhAkTNHbsWO3YsaPH/bW2tsrhcLg9AABwWbVK+sMfuv67o6PrX8Po+nf3bmn+fP/UBf9oaemaYxs4Sz4JzykpKSooKFBRUZF+85vfqKqqSjNmzFBDQ4Nqa2sVEhKiqKgot21GjRql2traHvf52GOPKTIy0vUYM2bMOT4LAEDAaGyUfvObrm/M86a9XXr3Xenzz31bF/zniiu8f2ELcJp8Mmxjzjd/dpGkyy+/XCkpKbrwwgv1+uuvK+wMx5w99NBDWrJkieu5w+EgQAMAuuza1fUVz72xWLr+/J+U5JOSAAwMfvmGwaioKF1yySXas2ePvvOd76itrU11dXVud58PHjzodYx0N5vNJpvN5oNqAQABp3t4xqnW+eUvpeef73qemSnV1UlTp3pf32rt+iropUu9t69c2fUhxIoK7/tITu76Nymp52OEhUkxMdKaNV1ffX0yu72rjsZG7/uIju76NzFRmjfP+zEyM7v+LSzsevTUHhXVdYz6eun4cfd1rVYpNlZ67TWprc2zlpUru9aprOy6w79pkzR8+D/au/siNlZh2dm6XtKw9PSusekn9sWQIV398MUXnsew27tm0Ghq6hrHbLG491l3XwB9zC/hubGxUV999ZWys7M1ZcoUDRkyRFu3btUt33x95u7du7V3716lpaX5ozwAQKC78kopNLRrnGtv3npLuvxy8/u9776uR28++aT39hdf7L39wgulm28+u2OsXt31OJt9dH+4rKhIKi2VTvqwmG6/vWvYS3V1V/vJ1q3rurOfmyvNnt31QcMTFRRIt9+u5qlT9fa3vqXjJSX/+MBgtxEjuvadmur9GHa79N//3XWc0NCu5yfy8sEw4Gz5ZMzz0qVLVVJSourqan300UeaO3eugoKCdOuttyoyMlILFizQkiVLtG3bNu3atUt33HGH0tLSmGkDAHBmIiOlBQvc72SeKDhYmjHj9IIzAMhHd56//vpr3XrrrTpy5IhGjhyp6dOnq7S0VCO/mSLo6aefltVq1S233KLW1lZlZmbq17/+tS9KAwAMVI8/Lv3pT9IHH3QNIej+8KDFIo0dK73yin/r66fq6ur0wgsv6L/+67909OhRnXfeebr44ovV0dGhoJ5+GQEGEZ+E51dffbXX9tDQUD3zzDN65plnfFEOAGAwGDZM2rpVevVVaf36ruEFI0d2/Wn/Jz+RTh4iAFVVVenqq6/W/v37JUmGYWjfvn0qLy9XS0uLfve732nIkCF+rhJnq7q6WgkJCdq2bZvHvMs4NZ/N8wwAgM+FhEg//rH04YfS/v1SebmUk0Nw9sIwDM2dO1e1tbUyDEPGNx+67Pzmjn1hYaH+7d/+zZ8loo9UVVUpKipKkydP9ncpAYnwDAAA9OGHH+pPf/qT6xv/TmYYhvLy8rx+BTMCyzvvvKOVK1fqvPPO83cpAckvs20AAID+Zfv27QoKClJH97cxenHs2DH90z/9k+s7GjIzM1VXV6epPUy9Z7VaFR8fr6U9TO+3cuVKhYaGSpLS09M9xlQnfzOlXVJSUo/HCAsLU0xMjNasWaN8L9P72e12Wa1WNTY2et1H9DdT2iUmJmpeD9P7ZX4zfV9hYaEKvUzv190eFRV1Vn0RFhamiooKr/voq76QpCeffNJt+WA5dzOvAzMshmFmMsz+z+FwKDIyUvX19Z5T3QAAgF6tWbNGjzzySK/hWZLKy8v79M/9XL8RaBi2AQAAlJGRccrgPGLECCXxjYwY5AjPAABAaWlpuuKKKxQc7H1Ep8Vi0U9/+lOFhIT4uDKgfyE8AwAAWSwWbdq0SXFxcbJYLK7l3eOQb7rpJq1cudJf5QH9Bh8YBAAAkqRx48bpL3/5iwoKClxfknLppZdq4cKFuuGGG2S1cs8N4AODAADAb7h+I9DwKyQAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAAAAYBLhGQAAADCJ8AwAAACYRHgGAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCTCMwAAAGAS4RkAAAAwifAMAAAAmER4BgAAAEwiPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwjMAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJOC/V0AAODcKSkp0aJFixQaGuq2vLOzU+np6dq5c6daW1s9tmtsbFRlZaXWrl2rDRs2KDjY/XLR1tamVatWKTU1VXPmzNHQoUM99pGQkKBNmzZp7ty5qqqq8mhvamrSli1bVFpaqtWrVyskJMStvb29XdnZ2crJydGkSZMUHh7usQ+bzaaysjItXrxYJSUlslrd7wm1tLRo/fr1ktRrP+Tl5SklJYW+8ENfdHZ2SpKmT58uq9Xq6ovExESPbYH+gPAMAANYc3OzsrKylJub67a8urpaK1askMViUXl5ucd2GRkZMgxDx44dU35+vjIyMtzaCwoK1NDQIKfTqWnTpqmgoMBjH6mpqZKkmpoar8ew2+1yOp1qaGjQsmXLZLfb3dqLi4tVVFQkwzAUHx+v4uLiHo9x+PBhbd68WePGjXNrz83NVXNzsyT12g+S6As/9YXD4VBkZKQ++OADRUREuPoC6K8YtgEAAACYRHgGAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCSmqgOAAeS9997T008/rZKSEknSxIkTNWHCBD9XBQADB+EZAAaIxx9/XCtWrFBQUJA6OjokSbt27dLHH3+syy67TMuWLfNzhQAQ+Bi2AQADQFlZmesLLrqDsyTXt7ctX75cO3fu9EttADCQEJ4BYAB45plnPL4q+UTBwcHKz8/3YUUAMDAxbAMABoCPPvpI7e3tPba3t7fr9ddf11//+lfXsszMTNXV1Wnq1Klet7FarYqPj9fSpUu9tq9cuVJhYWGqqKjwuo/k5GRJUlJSUo/HCAsLU0xMjNasWeM13NvtdlmtVjU2NnrdR3R0tCQpMTFR8+bN83qMzMxMSVJhYaEKCwt7bI+KiqIv/NAX3X8pSU9PV1BQkKSuvgD6K4thGIa/i+gLDodDkZGRqq+vV0REhL/LAQCfSkpK0hdffHHKdU4Mz0B/wPUbgYZhGwAwANxwww2uu3beBAUF6YYbbvBhRQAwMBGeAWAAuOeeezRkyBBZLBaPNqvVqiFDhujuu+/2Q2UAMLAQngFgABg3bpzefPNNhYaGymr9x//arVarQkND9eabb2rcuHH+KxAABgg+MAgAA8SsWbNUXV2t559/3vUlKRkZGVqwYIFGjhzp5+oAYGDgA4MAAMBvuH4j0DBsAwAAADCpX4XnZ555RuPGjVNoaKhSUlL4NiwAAAD0K/0mPL/22mtasmSJHn30UX366aeaPHmyMjMzdejQIX+XBgAAAEjqR+H5qaee0p133qk77rhDEydO1LPPPquhQ4fqhRde8HdpAAAAgKR+MttGW1ubdu3apYceesi1zGq1aubMmdqxY4fXbVpbW9Xa2up67nA4znmdAACcqKSkRIsWLVJoaKjb8s7OTqWnp2vnzp1u16pujY2Nqqys1Nq1a7VhwwYFB7tfjtva2rRq1SqlpqZqzpw5Gjp0qMc+EhIStGnTJs2dO1dVVVUe7U1NTdqyZYtKS0u1evVqhYSEuLW3t7crOztbOTk5mjRpksLDwz32YbPZVFZWpsWLF6ukpMRtGkRJamlp0fr16yWp137Iy8tTSkqK177ovn4//fTT2rhxo1/7Yvny5R7bnstz9+XrIDEx0aMNZ6ZfhOe///3v6ujo0KhRo9yWjxo1qsevm33sscf085//3BflAQDgVXNzs7KyspSbm+u2vLq6WitWrJDFYlF5ebnHdhkZGTIMQ8eOHVN+fr4yMjLc2gsKCtTQ0CCn06lp06apoKDAYx+pqamSpJqaGq/HsNvtcjqdamho0LJly2S3293ai4uLVVRUJMMwFB8fr+Li4h6PcfjwYW3evNljrvDc3Fw1NzdLUq/9IKnHvpgxY4aqqqpUV1fn977w5lyeuy9fB+g7/WbYxul66KGHVF9f73rs27fP3yUBAABggOsXd56jo6MVFBSkgwcPui0/ePCgYmNjvW5js9lks9l8UR4AAAAgqZ/ceQ4JCdGUKVO0detW17LOzk5t3bpVaWlpfqwMAAAA+Id+cedZkpYsWaLbb79dU6dO1VVXXaW1a9fq+PHjuuOOO/xdGgAAACCpH4XnH/7whzp8+LAeeeQR1dbW6oorrlBRUZHHhwgBAAAAf+k34VmS7rvvPt13333+LgMAAADwql+FZwAA+rOmpia98sorevnll3XkyBFFRkZq3LhxMgxDFovF3+UB8AHCMwAAJuzfv18ZGRnas2ePLBaLDMOQ1WrV9u3bZbFY9MILL3h8kQYCT3V1tRISErRt2zaPeZcBqZ/MtgEAQH9mGIZuvvlmVVdXu55LXTNDSdJvf/tb/fu//7u/ykMfqqqqUlRUlCZPnuzvUtBPEZ4BADiFsrIy7dy5U+3t7V7bDcPQU0891WM7Asc777yjlStX6rzzzvN3KeinGLYBAMApbN26VUFBQero6OhxnYMHD2ry5MkKCwuTJGVmZqqurk5Tp071ur7ValV8fLyWLl3qtX3lypUKCwtTRUWF130kJydLkpKSkno8RlhYmGJiYrRmzRrl5+d7tNvtdlmtVjU2NnrdR3R0tCQpMTFR8+bN83qMzMxMSVJhYaEKCwt7bI+KivJ6jO4+HT16tN/7QpKefPJJt+Xn8twl370O0HcsRvffngKcw+FQZGSk6uvrFRER4e9yAAADyC9+8Qv967/+6ynvLP/pT3/S5Zdf7qOqBgau3wg0DNsAAOAUvv3tb58yOEdGRuqSSy7xUUUA/IXwDADAKVx77bW69NJLFRQU5LXdarXqnnvuUWhoqI8rA+BrhGcAAE7BYrFo06ZNGjFihFuA7p6a7tprr9Wjjz7qr/IA+BDhGQAAE5KSklRRUaGHH35YF110kaKjo3XVVVepoKBA77zzjmw2m79LBOADfGAQAAD4DddvBBruPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwjMAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAAAAYBLhGQAAADCJ8AwAAACYRHgGAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCTCMwAAAGAS4RkAAAAwifAMAAAAmER4BgAAAEwiPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwjMAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAAAAYBLhGQAAADCJ8AwAAACYRHgGAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCTCMwAAAGAS4RkAAAAwifAMAAAAmER4BgAAAEzySXi22+2yWCxuj9mzZ7utc/ToUc2fP18RERGKiorSggUL1NjY6IvyAAAAAFOCfXWg2bNn68UXX3Q9t9lsbu3z589XTU2N3n33XTmdTt1xxx1auHChXn75ZV+VCAAAAPTKZ+HZZrMpNjbWa9vnn3+uoqIiffzxx5o6daokKS8vT9/97nf17//+74qLi/NVmQAAAECPfDbmubi4WDExMbr00kt1991368iRI662HTt2KCoqyhWcJWnmzJmyWq0qKyvzur/W1lY5HA63BwAAAHAu+SQ8z549W7/97W+1detWPf744yopKdGcOXPU0dEhSaqtrVVMTIzbNsHBwRoxYoRqa2u97vOxxx5TZGSk6zFmzJhzfh4AAAAY3Po8PL/00ksKDw93Pf74xz8qKytLN954o5KTk/X9739fhYWF+vjjj1VcXHzGx3nooYdUX1/veuzbt6/vTgIAAADwos/HPN94441KSUlxPR89erTHOuPHj1d0dLT27Nmj6667TrGxsTp06JDbOu3t7Tp69GiP46RtNpvHhw4BAACAc6nPw/Pw4cM1fPjwXtf5+uuvdeTIEV1wwQWSpLS0NNXV1WnXrl2aMmWKJOn9999XZ2enWxAHAAAA/Omcj3lubGzUgw8+qNLSUlVXV2vr1q266aabdNFFFykzM1OSlJSUpNmzZ+vOO+/Uzp079eGHH+q+++5TVlYWM20AAACg3zjn4TkoKEh//vOfdeONN+qSSy7RggULNGXKFP3xj390G3bx0ksvacKECbruuuv03e9+V9OnT9dzzz13rssDAAAATLMYhmH4u4i+4HA4FBkZqfr6ekVERPi7HAAAYALXbwQan83zDAAAAAQ6wjMAAABgEuEZAAAAMInwDAAAAJjU5/M8A2erpKREixYtUmhoqNvyzs5Opaena+fOnWptbfXYrrGxUZWVlVq7dq02bNig4GD3l3dbW5tWrVql1NRUzZkzR0OHDvXYR0JCgjZt2qS5c+eqqqrKo72pqUlbtmxRaWmpVq9erZCQELf29vZ2ZWdnKycnR5MmTVJ4eLjHPmw2m8rKyrR48WKVlJTIanX/HbalpUXr16+XpF77IS8vTykpKYOiL9LT0z22BQDAHwjP6Heam5uVlZWl3Nxct+XV1dVasWKFLBaLysvLPbbLyMiQYRg6duyY8vPzlZGR4dZeUFCghoYGOZ1OTZs2TQUFBR77SE1NlSTV1NR4PYbdbpfT6VRDQ4OWLVsmu93u1l5cXKyioiIZhqH4+HivX0HffYzDhw9r8+bNGjdunFt7bm6umpubJanXfpA0qPoCAID+gGEbAAAAgEmEZwAAAMAkviSlH2CMr/sY37a2NjU1NSk2NtatHx544AFNmTJFLS0tuvjiiz36Ii4uTrNmzdKvfvUrRUZGutXS1tamGTNmKD4+Xs8//7wcDofGjh3r0Rc1NTW64IIL9Ic//MHjGE1NTUpOTlZqaqqeeuopDRkyRCNGjHDri2nTpikyMlK/+93vdOjQIV100UUefWGxWPStb31LGzZsUFxcnFuftrS0KDU1VRMnTlReXp6cTqerH7r74sorr1Rra6uqqqpUUVExKPrihRdeOKdjv+fPn++xLQDfCOTrNwYnxjz3A4zxdR/jm5qaqtLSUld/nDjGV5KSk5NVWlrq0RednZ2qq6vTd77zHS1cuNCtPwoKCrRt2zZ1dHToyiuvVGRkpEd/nNgX3o5ht9tVX1+v48ePa9asWbrmmmvc+qO4uFjPPfecIiIiFB8fr7Fjx3r0x4l9MWPGDOXl5bn1R25urvbs2aO2tjalp6froosucntdVFdXa/HixRo2bJgsFsug6YtzPfYbAACzGLYBAAAAmMSdZ/idYRjatWuXvvrqKx04cMBjCAEAAEB/QXiGX3388cf61a9+pfr6elmtVnV2dup//ud/NGHCBD3wwAMaPny4v0sEAABwYdgG/ObLL7/UNddcI4fDIanrA2Dddu/ere9///saIJ9nBQAAAwThGX7z+OOPq7W11WtANgxD77//vkpKSvxQGQAAgHcM2/CT5uZmbdy4UX/961914MABr1O8DWSGYejll19We3t7j+sEBwfr5Zdf1sqVK31YGQAAQM8Iz37w1ltvKTs7W/X19RoyZIg6OjrU2dmp/fv366WXXhoUQdrpdJ7ya5fb29u1ceNGlZaW6uuvv9aePXsUGhqqqKgoTZ061W3d3bt365JLLpHFYtHIkSO1dOlSt/YjR46os7NTU6ZMUVBQkCoqKjz28cUXX+gHP/iBPv/8cyUlJXm0V1dXKzY2VlOnTtXw4cOVn5+v/Px8V3tDQ4McDoeWLVsmqWuOYW/HmD59uiRp7Nixmjdvnlt79y9SU6ZMkc1mU2FhoQoLC13tbW1t+vrrr3X33Xerurp60PRFfX29AADoDwjPPvbRRx9p7ty5rvG9TqfT1fb222/rn//5n/XOO+/4qzyfCQkJUUxMjA4dOtTjOsHBwbrzzjt1zz33aMWKFXr11VeVmpqqoqIij3UzMjJUVFSk3NxczZ07V7/61a/c2gsKCtTS0qKMjAx9+umn+uSTTzz2kZqaqhdffNH178nsdrtWrFih4uJijR492i0sSv+Y8/ruu+/Wm2++2eMxioqKlJWVpQcffNDrnNfd8x/X19fr+eefd2vvntt49erV2rp166Dpi5PnmQYAwF8Y8+xj//qv/ypJXsf5dnR0aMuWLfr44499XZZf3HXXXQoKCuqxvb29XT/5yU98WBEAAEDvCM8+1NDQoP/5n/9RR0dHj+sEBwdr48aNPqzKf5YsWaKLL75YFovFa/vy5cs1YcIEH1cFAADQM4Zt+FBjY+Mpp17r6OjQiy++qPfff1+SlJmZqbq6Oo/xot2sVqvi4+M9xrV2W7lypcLCwryOa5W6vupaktdxrd3CwsIUExOjNWvWePx5Xur6E77VavU6rlWSoqOjJUmJiYke41ptNptGjBih+vp614cHhwwZotjYWL333nuu/WVmZkqS1zG+A6UvunWf68njnU9upy/6ri8AADDLYgyQiXQdDociIyNVX1+viIgIf5fjldPpVHR0tGteY2+sVquefPJJLVmyxIeV+V9dXZ12796t0NBQXXbZZb0O5wAADByBcP0GTsSwDR8aMmSI/uVf/qXXYBgUFKTs7GwfVtU/REVFKSUlRZMnTyY4AwCAfovw7GOrVq1SYmKiR0C0Wrt+FHl5eRo5cqQ/SgMAAMApEJ59bMSIEfroo4+0cOFChYWFuZZffvnl+v3vf69Fixb5sToAAAD0hjHPfnT8+HHt27dPw4YN05gxY/xdDgAAPheI128Mbsy24UfDhg1jKjYAAIAAwrANAAAAwCTuPAMA8I2SkhItWrRIoaGhbss7OzuVnp6unTt3qrW11WO7xsZGVVZWau3atdqwYYOCg90vr21tbVq1apVSU1M1Z84cDR061GMfCQkJ2rRpk+bOnauqqiqP9qamJm3ZskWlpaVavXq1QkJC3Nrb29uVnZ2tnJwcTZo0SeHh4R77sNlsKisr0+LFi1VSUuL6sHq3lpYWrV+/XpJ67Ye8vDylpKT0SV90H2P69OmuegKtLzC4EJ4BAPhGc3OzsrKylJub67a8urpaK1askMViUXl5ucd2GRkZMgxDx44dU35+vjIyMtzaCwoK1NDQIKfTqWnTpqmgoMBjH6mpqZKkmpoar8ew2+1yOp1qaGjQsmXLZLfb3dqLi4tVVFQkwzAUHx+v4uLiHo9x+PBhbd68WePGjXNrz83NVXNzsyT12g+S+qwv1q1bp8jISH3wwQeuMc+B1hcYXBi2AQAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAGDQcjgceuyxxzRu3DiFhITotttu03vvvafa2lp/lwagn2KeZwDAoPT3v/9d06dP15dffqnOzk5J0rFjx/TRRx/piiuu0IcffqjExEQ/Vwmgv+HOMwBgUFq8eLH27NnjCs7dDMPQ3//+d916661+qgxAf0Z4BgAMOgcPHtTGjRvV0dHhtb2jo0Mff/yxPv30Ux9XBqC/Y9gGAGDQKS8v7zE4n2ju3LkaOXKkJCkzM1N1dXWaOnWq13WtVqvi4+O1dOlSr+0rV65UWFiYKioqvO4jOTlZkpSUlNTjMcLCwhQTE6M1a9YoPz/fo91ut8tqtaqxsdHrPqKjoyVJiYmJmjdvntdjZGZmSpIKCwtVWFjYY3tUVFSf9EV6erokKT09XUFBQZICry8wuFgMwzD8XURfcDgcioyMVH19vSIiIvxdDgCgH9u2bZuuvfbaU673wgsv6I477vBBRYMX128EGoZtAAAGnZSUFA0fPrzXdaxWq77zne/4qCIAgYLwDAAYdIYOHaqf/exnslgsXtuDgoKUlZWl+Ph4H1cGoL8jPAMABqVHH31Ut912myQpOLjrI0DdY25nzJih9evX+602AP0XY54BAIOWYRjasWOHnn/+ef3tb3/TqFGjlJ2drVmzZslq5f6SL3D9RqBhtg0AwKBlsVg0bdo0TZs2zd+lAAgQ/FoNAAAAmER4BgAAAEwiPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwjMAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJPOOjy/8cYbmjVrls4//3xZLBaVl5d7rNPS0qJ7771X559/vsLDw3XLLbfo4MGDbuvs3btX119/vYYOHaqYmBg9+OCDam9vP9vyAAAAgD5z1uH5+PHjmj59uh5//PEe17n//vv11ltvaePGjSopKdGBAwd08803u9o7Ojp0/fXXq62tTR999JH+8z//UwUFBXrkkUfOtjwAAACgz1gMwzD6YkfV1dVKSEjQZ599piuuuMK1vL6+XiNHjtTLL7+sefPmSZK++OILJSUlaceOHUpNTdWWLVv0ve99TwcOHNCoUaMkSc8++6yWL1+uw4cPKyQk5JTHdzgcioyMVH19vSIiIvrilAAAwDnG9RuB5pyPed61a5ecTqdmzpzpWjZhwgSNHTtWO3bskCTt2LFDycnJruAsSZmZmXI4HKqsrPS639bWVjkcDrcHAAAAcC6d8/BcW1urkJAQRUVFuS0fNWqUamtrXeucGJy727vbvHnssccUGRnpeowZM6bviwcAAABOcFrh+aWXXlJ4eLjr8cc//vFc1XVKDz30kOrr612Pffv2+a0WAAAADA7Bp7PyjTfeqJSUFNfz0aNHn3Kb2NhYtbW1qa6uzu3u88GDBxUbG+taZ+fOnW7bdc/G0b3OyWw2m2w22+mUDwAAAJyV07rzPHz4cF100UWuR1hY2Cm3mTJlioYMGaKtW7e6lu3evVt79+5VWlqaJCktLU1/+ctfdOjQIdc67777riIiIjRx4sTTKREAAAA4Z07rzrM3R48e1d69e3XgwAFJXcFY6rpjHBsbq8jISC1YsEBLlizRiBEjFBERocWLFystLU2pqamSpFmzZmnixInKzs7WE088odraWv2f//N/dO+993J3GQAAAP3GWX9gcPPmzbryyit1/fXXS5KysrJ05ZVX6tlnn3Wt8/TTT+t73/uebrnlFl199dWKjY3VG2+84WoPCgpSYWGhgoKClJaWph/96Ef68Y9/rF/84hdnWx4AAADQZ/psnmd/Y55IAAACD9dvBJpzPlUdAAAAMFAQngEAAACTCM8AAACASYRnAAAAwCTCMwAAAGAS4RkAAAAw6ay/JGWwKCkp0aJFixQaGuq2vLOzU+np6dq5c6daW1s9tmtsbFRlZaXWrl2rDRs2KDjYvcvb2tq0atUqpaamas6cORo6dKjHPhISErRp0ybNnTtXVVVVHu1NTU3asmWLSktLtXr1aoWEhLi1t7e3Kzs7Wzk5OZo0aZLCw8M99mGz2VRWVqbFixerpKREVqv771UtLS1av369JPXaD3l5eUpJSaEvfNgXAADAdwjPJjU3NysrK0u5ubluy6urq7VixQpZLBaVl5d7bJeRkSHDMHTs2DHl5+crIyPDrb2goEANDQ1yOp2aNm2aCgoKPPbR/U2MNTU1Xo9ht9vldDrV0NCgZcuWyW63u7UXFxerqKhIhmEoPj5excXFPR7j8OHD2rx5s8aNG+fWnpubq+bmZknqtR8k0Rc+7gsAAOA7DNsAAAAATCI8AwAAACYRngEAAACTCM8AAACASYRnAAAAwCRm2+hFe3u7tm3bpgMHDujrr79WZ2env0sCAACAHxGee/Df//3f+ulPf6qamhrXsmHDhmnChAm67bbb/FgZAAAA/IXw7MUbb7yhH/zgBx7Ljx8/rvnz50sSARoAAGAQYszzSTo7O3X//ff3us4DDzyg9vZ2H1UEAACA/oLwfJIPP/xQe/fu7XWd2tpabdu2zUcVAQAAoL9g2MZJamtrTa23cOFCnX/++ZKkzMxM1dXVaerUqV7XtVqtio+P19KlS722r1y5UmFhYaqoqPC6j+TkZElSUlJSj8cICwtTTEyM1qxZo/z8fI92u90uq9WqxsZGr/uIjo6WJCUmJmrevHlej5GZmSlJKiwsVGFhYY/tUVFR9IUP+wIAAPiOxTAMw99F9AWHw6HIyEjV19crIiLijPfz0Ucf6dvf/vYp13vvvfd03XXXnfFxAABA312/AV9h2MZJUlNTNX78eFkslh7XGT16tDIyMnxXFAAAAPoFwvNJrFar1q1bJ0keAdpischisWjdunUKCgryR3kAAADwI8KzF9dff70KCws1fvx4t+UXXnih3njjDd18881+qgwAAAD+xJjnXhiGobKyMu3fv1+xsbFKS0uT1crvGwAA9BXGPCPQMNtGLywWi1JTU/1dBgAAAPoJbqMCAAAAJhGeAQAAAJMIzwAAAIBJhGcAAADAJMIzAAAAYBLhGQAAADCJ8AwAAACYRHgGAAAATCI8AwAAACYNmG8Y7P6WcYfD4edKAACAWd3X7e7rONDfDZjw3NDQIEkaM2aMnysBAACnq6GhQZGRkf4uAzglizFAftXr7OzUgQMHNHz4cFksFn+XI4fDoTFjxmjfvn2KiIjwdzk+MxjPm3PmnAeqwXjO0uA8b3+es2EYamhoUFxcnKxWRpOi/xswd56tVqvi4+P9XYaHiIiIQfM/3xMNxvPmnAcHznnwGIzn7a9z5o4zAgm/4gEAAAAmEZ4BAAAAkwjP54jNZtOjjz4qm83m71J8ajCeN+c8OHDOg8dgPO/BeM7AmRowHxgEAAAAzjXuPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwvNpcjqdWr58uZKTkzVs2DDFxcXpxz/+sQ4cOOC23tGjRzV//nxFREQoKipKCxYsUGNjo9s6f/7znzVjxgyFhoZqzJgxeuKJJ3x5KqftjTfe0KxZs3T++efLYrGovLzcY52MjAxZLBa3x1133eW2zt69e3X99ddr6NChiomJ0YMPPqj29nYfncXpMXPOLS0tuvfee3X++ecrPDxct9xyiw4ePOi2TiCd88nsdrvHz3T27Nlu65h5vQe6Z555RuPGjVNoaKhSUlK0c+dOf5fUZ3Jzcz1+xhMmTHC1m3mN93fbt2/XDTfcoLi4OFksFv3+9793azcMQ4888oguuOAChYWFaebMmfryyy/d1gm01/mpzpn3NnBmCM+nqampSZ9++qkefvhhffrpp3rjjTe0e/du3XjjjW7rzZ8/X5WVlXr33XdVWFio7du3a+HCha52h8OhWbNm6cILL9SuXbv05JNPKjc3V88995yvT8m048ePa/r06Xr88cd7Xe/OO+9UTU2N63HiLwUdHR26/vrr1dbWpo8++kj/+Z//qYKCAj3yyCPnuvwzYuac77//fr311lvauHGjSkpKdODAAd18882u9kA7Z29mz57t9jN95ZVX3NpP9XoPdK+99pqWLFmiRx99VJ9++qkmT56szMxMHTp0yN+l9ZlJkya5/Yw/+OADV9upXuOB4Pjx45o8ebKeeeYZr+1PPPGE1q1bp2effVZlZWUaNmyYMjMz1dLS4lon0F7npzpnifc2cEYMnLWdO3cakoy//e1vhmEYxl//+ldDkvHxxx+71tmyZYthsViM/fv3G4ZhGL/+9a+N8847z2htbXWts3z5cuPSSy/1bfFnoKqqypBkfPbZZx5t6enpxs9+9rMet33nnXcMq9Vq1NbWupb95je/MSIiItz6or/p6Zzr6uqMIUOGGBs3bnQt+/zzzw1Jxo4dOwzDCNxz7nb77bcbN910U4/tZl7vge6qq64y7r33Xtfzjo4OIy4uznjsscf8WFXfefTRR43Jkyd7bTPzGg80koxNmza5nnd2dhqxsbHGk08+6VpWV1dn2Gw245VXXjEMI/Bf5yefs2Hw3gbOFHee+0B9fb0sFouioqIkSTt27FBUVJSmTp3qWmfmzJmyWq0qKytzrXP11VcrJCTEtU5mZqZ2796tY8eO+bT+vvbSSy8pOjpal112mR566CE1NTW52nbs2KHk5GSNGjXKtSwzM1MOh0OVlZX+KPes7Nq1S06nUzNnznQtmzBhgsaOHasdO3ZIGhjnXFxcrJiYGF166aW6++67deTIEVebmdd7IGtra9OuXbvcfsZWq1UzZ850/YwHgi+//FJxcXEaP3685s+fr71790oy9xoPdFVVVaqtrXU7x8jISKWkpLi9jwfi63wwv7eBMxXs7wICXUtLi5YvX65bb71VERERkqTa2lrFxMS4rRccHKwRI0aotrbWtU5CQoLbOt3hqra2Vuedd54Pqu97t912my688ELFxcXpz3/+s5YvX67du3frjTfekNR1bieGSMn9vANNbW2tQkJCXL84dRs1apTbzzqQz3n27Nm6+eablZCQoK+++korV67UnDlztGPHDgUFBZl6vQeyv//97+ro6PD6M/ziiy/8VFXfSklJUUFBgS699FLV1NTo5z//uWbMmKGKigpTr/FA130e3n7GJ76PB9rrfLC/t4EzRXg+hZdeekmLFi1yPd+yZYtmzJghqevDg//8z/8swzD0m9/8xl8lnhO9nXdvThwLl5ycrAsuuEDXXXedvvrqKyUmJp6TWvvKmZ7zQOKtD7KyslzPk5OTdfnllysxMVHFxcW67rrr/FEm+ticOXNc/3355ZcrJSVFF154oV5//XWFhYX5sTKcS7y3gTNDeD6FG2+8USkpKa7no0ePlvSP4Py3v/1N77//vuuusyTFxsZ6fJCovb1dR48eVWxsrGudkz+t3v28ex1/6um8T1f3Pvbs2aPExETFxsZ6zFLQX877TM45NjZWbW1tqqurc7szd/DgQbefdX8955OZ6YPx48crOjpae/bs0XXXXWfq9R7IoqOjFRQU5PX9OhDOz5uoqChdcskl2rNnj77zne+c8jUe6LrP4+DBg7rgggtcyw8ePKgrrrjCtc5Afp1Lg++9DZwpxjyfwvDhw3XRRRe5HmFhYa7g/OWXX+q9997T+eef77ZNWlqa6urqtGvXLtey999/X52dna5gkpaWpu3bt8vpdLrWeffdd3XppZf2iyEb3s77THRP7dZ9QUpLS9Nf/vIXt/8hv/vuu4qIiNDEiRPPuu6zcSbnPGXKFA0ZMkRbt251Ldu9e7f27t2rtLQ0Sf37nE9mpg++/vprHTlyxO1neqrXeyALCQnRlClT3H7GnZ2d2rp1q+tnPNA0Njbqq6++0gUXXGDqNR7oEhISFBsb63aODodDZWVlbu/jgfw6lwbfexs4Y/7+xGKgaWtrM2688UYjPj7eKC8vN2pqalyPE2dOmD17tnHllVcaZWVlxgcffGBcfPHFxq233upqr6urM0aNGmVkZ2cbFRUVxquvvmoMHTrUWL9+vT9Oy5QjR44Yn332mfH2228bkoxXX33V+Oyzz4yamhrDMAxjz549xi9+8Qvjk08+Maqqqow333zTGD9+vHH11Ve79tHe3m5cdtllxqxZs4zy8nKjqKjIGDlypPHQQw/567R6dapzNgzDuOuuu4yxY8ca77//vvHJJ58YaWlpRlpamqs90M75RA0NDcbSpUuNHTt2GFVVVcZ7771n/NM//ZNx8cUXGy0tLa71TvV6D3SvvvqqYbPZjIKCAuOvf/2rsXDhQiMqKsptBpVA9sADDxjFxcVGVVWV8eGHHxozZ840oqOjjUOHDhmGcerXeCBoaGgwPvvsM+Ozzz4zJBlPPfWU8dlnn7lmSfrlL39pREVFGW+++abx5z//2bjpppuMhIQEo7m52bWPQHud93bOvLeBM0d4Pk3dU5Z5e2zbts213pEjR4xbb73VCA8PNyIiIow77rjDaGhocNvXn/70J2P69OmGzWYzRo8ebfzyl7/08dmcnhdffNHreT/66KOGYRjG3r17jauvvtoYMWKEYbPZjIsuush48MEHjfr6erf9VFdXG3PmzDHCwsKM6Oho44EHHjCcTqcfzujUTnXOhmEYzc3Nxj333GOcd955xtChQ425c+e6hWvDCKxzPlFTU5Mxa9YsY+TIkcaQIUOMCy+80Ljzzjs9QqOZ13ugy8vLM8aOHWuEhIQYV111lVFaWurvkvrMD3/4Q+OCCy4wQkJCjNGjRxs//OEPjT179rjazbzG+7tt27Z5fS/ffvvthmF0TVf38MMPG6NGjTJsNptx3XXXGbt373bbR6C9zns7Z97bwJmzGIZh+OIONwAAABDoGPMMAAAAmER4BgAAAEwiPAMAAAAmEZ4BAAAAkwjPAAAAgEmEZwAAAMAkwjMAAABgEuEZAAAAMInwDAAAAJhEeAYAAABMIjwDAAAAJhGeAQAAAJP+P3OsMs5EXG2oAAAAAElFTkSuQmCC\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['Kaitt', 'SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "\n",
    "color_list =  ['black'] * len(embeddings_2d[1:])\n",
    "color_list.insert(0, 'red')\n",
    "\n",
    "plt.scatter(embeddings_2d[:, 0], embeddings_2d[:, 1] , color=color_list )\n",
    "\n",
    "for i in range(len(embeddings_2d)):\n",
    "    plt.text(embeddings_2d[:,0][i], embeddings_2d[:,1][i]+2,  sentences[i] ,color=color_list[i] )\n",
    "\n",
    "# 显示图表\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "y0HxG9NeNYOv"
   },
   "source": [
    "## openai text-embedding-ada-002 embedding模型"
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "! pip install openai==0.28"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0ngLP4sPPTjm",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327226,
     "user_tz": -60,
     "elapsed": 16928,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "865ec125-b21d-4b24-beb3-fc47a15956f7"
   },
   "execution_count": 9,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Collecting openai==0.28\n",
      "  Downloading openai-0.28.0-py3-none-any.whl (76 kB)\n",
      "\u001B[?25l     \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m0.0/76.5 kB\u001B[0m \u001B[31m?\u001B[0m eta \u001B[36m-:--:--\u001B[0m\r\u001B[2K     \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m76.5/76.5 kB\u001B[0m \u001B[31m2.6 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\n",
      "\u001B[?25hRequirement already satisfied: requests>=2.20 in /usr/local/lib/python3.10/dist-packages (from openai==0.28) (2.31.0)\n",
      "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai==0.28) (4.66.4)\n",
      "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from openai==0.28) (3.9.5)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai==0.28) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai==0.28) (3.7)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai==0.28) (2.0.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai==0.28) (2024.2.2)\n",
      "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (1.3.1)\n",
      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (23.2.0)\n",
      "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (1.4.1)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (6.0.5)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (1.9.4)\n",
      "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai==0.28) (4.0.3)\n",
      "Installing collected packages: openai\n",
      "Successfully installed openai-0.28.0\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "HEq-ZaxfNYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327226,
     "user_tz": -60,
     "elapsed": 21,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    }
   },
   "outputs": [],
   "source": [
    "import openai\n",
    "import os\n",
    "OPENAI_API_KEY = getpass()\n",
    "\n",
    "openai.api_key = OPENAI_API_KEY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "46PUukzrNYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327732,
     "user_tz": -60,
     "elapsed": 525,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    }
   },
   "outputs": [],
   "source": [
    "import openai\n",
    "response = openai.Embedding.create(\n",
    "  input=sentences,\n",
    "  model=\"text-embedding-ada-002\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "F-zP71IINYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327995,
     "user_tz": -60,
     "elapsed": 267,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    }
   },
   "outputs": [],
   "source": [
    "embeddings_openai = [item['embedding'] for item in response['data']]\n",
    "\n",
    "tsne = TSNE(n_components=2 ,  perplexity=5)\n",
    "embeddings_openai_2d = tsne.fit_transform(np.array(embeddings_openai))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "CIp9urkbNYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327995,
     "user_tz": -60,
     "elapsed": 9,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "fc553455-8b62-4519-9057-e26fc7fe0219"
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "metadata": {},
     "execution_count": 13
    }
   ],
   "source": [
    "len(embeddings_openai)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "VjVnBU4ZNYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190327995,
     "user_tz": -60,
     "elapsed": 6,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "outputId": "c4bc51af-ec6b-4b67-ce25-70a489ea845d"
   },
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "1536"
      ]
     },
     "metadata": {},
     "execution_count": 14
    }
   ],
   "source": [
    "len(embeddings_openai[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "id": "GKLYFwfkNYOw",
    "executionInfo": {
     "status": "ok",
     "timestamp": 1715190329227,
     "user_tz": -60,
     "elapsed": 1236,
     "user": {
      "displayName": "yuhao li",
      "userId": "05587000238808101215"
     }
    },
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "outputId": "d03d257f-c322-492b-b3ab-28a2e16fb127"
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20026 (\\N{CJK UNIFIED IDEOGRAPH-4E3A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20160 (\\N{CJK UNIFIED IDEOGRAPH-4EC0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20040 (\\N{CJK UNIFIED IDEOGRAPH-4E48}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33391 (\\N{CJK UNIFIED IDEOGRAPH-826F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22909 (\\N{CJK UNIFIED IDEOGRAPH-597D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30340 (\\N{CJK UNIFIED IDEOGRAPH-7684}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30561 (\\N{CJK UNIFIED IDEOGRAPH-7761}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30496 (\\N{CJK UNIFIED IDEOGRAPH-7720}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23545 (\\N{CJK UNIFIED IDEOGRAPH-5BF9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20581 (\\N{CJK UNIFIED IDEOGRAPH-5065}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24247 (\\N{CJK UNIFIED IDEOGRAPH-5EB7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33267 (\\N{CJK UNIFIED IDEOGRAPH-81F3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20851 (\\N{CJK UNIFIED IDEOGRAPH-5173}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 37325 (\\N{CJK UNIFIED IDEOGRAPH-91CD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35201 (\\N{CJK UNIFIED IDEOGRAPH-8981}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26377 (\\N{CJK UNIFIED IDEOGRAPH-6709}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21161 (\\N{CJK UNIFIED IDEOGRAPH-52A9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20110 (\\N{CJK UNIFIED IDEOGRAPH-4E8E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36523 (\\N{CJK UNIFIED IDEOGRAPH-8EAB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20307 (\\N{CJK UNIFIED IDEOGRAPH-4F53}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20462 (\\N{CJK UNIFIED IDEOGRAPH-4FEE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22797 (\\N{CJK UNIFIED IDEOGRAPH-590D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33258 (\\N{CJK UNIFIED IDEOGRAPH-81EA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22686 (\\N{CJK UNIFIED IDEOGRAPH-589E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24378 (\\N{CJK UNIFIED IDEOGRAPH-5F3A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20813 (\\N{CJK UNIFIED IDEOGRAPH-514D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30123 (\\N{CJK UNIFIED IDEOGRAPH-75AB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31995 (\\N{CJK UNIFIED IDEOGRAPH-7CFB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32479 (\\N{CJK UNIFIED IDEOGRAPH-7EDF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22312 (\\N{CJK UNIFIED IDEOGRAPH-5728}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30417 (\\N{CJK UNIFIED IDEOGRAPH-76D1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30563 (\\N{CJK UNIFIED IDEOGRAPH-7763}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23398 (\\N{CJK UNIFIED IDEOGRAPH-5B66}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20064 (\\N{CJK UNIFIED IDEOGRAPH-4E60}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20013 (\\N{CJK UNIFIED IDEOGRAPH-4E2D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 65292 (\\N{FULLWIDTH COMMA}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31639 (\\N{CJK UNIFIED IDEOGRAPH-7B97}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27861 (\\N{CJK UNIFIED IDEOGRAPH-6CD5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32463 (\\N{CJK UNIFIED IDEOGRAPH-7ECF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24120 (\\N{CJK UNIFIED IDEOGRAPH-5E38}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38656 (\\N{CJK UNIFIED IDEOGRAPH-9700}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22823 (\\N{CJK UNIFIED IDEOGRAPH-5927}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 37327 (\\N{CJK UNIFIED IDEOGRAPH-91CF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26631 (\\N{CJK UNIFIED IDEOGRAPH-6807}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35760 (\\N{CJK UNIFIED IDEOGRAPH-8BB0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25968 (\\N{CJK UNIFIED IDEOGRAPH-6570}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25454 (\\N{CJK UNIFIED IDEOGRAPH-636E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26469 (\\N{CJK UNIFIED IDEOGRAPH-6765}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36827 (\\N{CJK UNIFIED IDEOGRAPH-8FDB}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 34892 (\\N{CJK UNIFIED IDEOGRAPH-884C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25928 (\\N{CJK UNIFIED IDEOGRAPH-6548}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36275 (\\N{CJK UNIFIED IDEOGRAPH-8DB3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21487 (\\N{CJK UNIFIED IDEOGRAPH-53EF}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33021 (\\N{CJK UNIFIED IDEOGRAPH-80FD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23548 (\\N{CJK UNIFIED IDEOGRAPH-5BFC}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33268 (\\N{CJK UNIFIED IDEOGRAPH-81F4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38271 (\\N{CJK UNIFIED IDEOGRAPH-957F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26399 (\\N{CJK UNIFIED IDEOGRAPH-671F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38382 (\\N{CJK UNIFIED IDEOGRAPH-95EE}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 39064 (\\N{CJK UNIFIED IDEOGRAPH-9898}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22914 (\\N{CJK UNIFIED IDEOGRAPH-5982}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24515 (\\N{CJK UNIFIED IDEOGRAPH-5FC3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33039 (\\N{CJK UNIFIED IDEOGRAPH-810F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30149 (\\N{CJK UNIFIED IDEOGRAPH-75C5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21644 (\\N{CJK UNIFIED IDEOGRAPH-548C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31958 (\\N{CJK UNIFIED IDEOGRAPH-7CD6}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23615 (\\N{CJK UNIFIED IDEOGRAPH-5C3F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36825 (\\N{CJK UNIFIED IDEOGRAPH-8FD9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31181 (\\N{CJK UNIFIED IDEOGRAPH-79CD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26041 (\\N{CJK UNIFIED IDEOGRAPH-65B9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20381 (\\N{CJK UNIFIED IDEOGRAPH-4F9D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36182 (\\N{CJK UNIFIED IDEOGRAPH-8D56}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36136 (\\N{CJK UNIFIED IDEOGRAPH-8D28}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23427 (\\N{CJK UNIFIED IDEOGRAPH-5B83}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24110 (\\N{CJK UNIFIED IDEOGRAPH-5E2E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32500 (\\N{CJK UNIFIED IDEOGRAPH-7EF4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25345 (\\N{CJK UNIFIED IDEOGRAPH-6301}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27491 (\\N{CJK UNIFIED IDEOGRAPH-6B63}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26032 (\\N{CJK UNIFIED IDEOGRAPH-65B0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38472 (\\N{CJK UNIFIED IDEOGRAPH-9648}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20195 (\\N{CJK UNIFIED IDEOGRAPH-4EE3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35874 (\\N{CJK UNIFIED IDEOGRAPH-8C22}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25511 (\\N{CJK UNIFIED IDEOGRAPH-63A7}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21046 (\\N{CJK UNIFIED IDEOGRAPH-5236}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20799 (\\N{CJK UNIFIED IDEOGRAPH-513F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 31461 (\\N{CJK UNIFIED IDEOGRAPH-7AE5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38738 (\\N{CJK UNIFIED IDEOGRAPH-9752}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23569 (\\N{CJK UNIFIED IDEOGRAPH-5C11}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24180 (\\N{CJK UNIFIED IDEOGRAPH-5E74}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 33041 (\\N{CJK UNIFIED IDEOGRAPH-8111}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21457 (\\N{CJK UNIFIED IDEOGRAPH-53D1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32946 (\\N{CJK UNIFIED IDEOGRAPH-80B2}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25104 (\\N{CJK UNIFIED IDEOGRAPH-6210}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23588 (\\N{CJK UNIFIED IDEOGRAPH-5C24}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25552 (\\N{CJK UNIFIED IDEOGRAPH-63D0}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 39640 (\\N{CJK UNIFIED IDEOGRAPH-9AD8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26085 (\\N{CJK UNIFIED IDEOGRAPH-65E5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38388 (\\N{CJK UNIFIED IDEOGRAPH-95F4}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24037 (\\N{CJK UNIFIED IDEOGRAPH-5DE5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20316 (\\N{CJK UNIFIED IDEOGRAPH-4F5C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29575 (\\N{CJK UNIFIED IDEOGRAPH-7387}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27880 (\\N{CJK UNIFIED IDEOGRAPH-6CE8}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24847 (\\N{CJK UNIFIED IDEOGRAPH-610F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21147 (\\N{CJK UNIFIED IDEOGRAPH-529B}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21151 (\\N{CJK UNIFIED IDEOGRAPH-529F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21462 (\\N{CJK UNIFIED IDEOGRAPH-53D6}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20915 (\\N{CJK UNIFIED IDEOGRAPH-51B3}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29305 (\\N{CJK UNIFIED IDEOGRAPH-7279}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 24449 (\\N{CJK UNIFIED IDEOGRAPH-5F81}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 36873 (\\N{CJK UNIFIED IDEOGRAPH-9009}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25321 (\\N{CJK UNIFIED IDEOGRAPH-62E9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23376 (\\N{CJK UNIFIED IDEOGRAPH-5B50}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35745 (\\N{CJK UNIFIED IDEOGRAPH-8BA1}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26426 (\\N{CJK UNIFIED IDEOGRAPH-673A}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 23637 (\\N{CJK UNIFIED IDEOGRAPH-5C55}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20173 (\\N{CJK UNIFIED IDEOGRAPH-4ECD}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22788 (\\N{CJK UNIFIED IDEOGRAPH-5904}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26089 (\\N{CJK UNIFIED IDEOGRAPH-65E9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38454 (\\N{CJK UNIFIED IDEOGRAPH-9636}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 27573 (\\N{CJK UNIFIED IDEOGRAPH-6BB5}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 38754 (\\N{CJK UNIFIED IDEOGRAPH-9762}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20020 (\\N{CJK UNIFIED IDEOGRAPH-4E34}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25216 (\\N{CJK UNIFIED IDEOGRAPH-6280}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 26415 (\\N{CJK UNIFIED IDEOGRAPH-672F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29289 (\\N{CJK UNIFIED IDEOGRAPH-7269}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29702 (\\N{CJK UNIFIED IDEOGRAPH-7406}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25361 (\\N{CJK UNIFIED IDEOGRAPH-6311}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25112 (\\N{CJK UNIFIED IDEOGRAPH-6218}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 19982 (\\N{CJK UNIFIED IDEOGRAPH-4E0E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20256 (\\N{CJK UNIFIED IDEOGRAPH-4F20}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21516 (\\N{CJK UNIFIED IDEOGRAPH-540C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 21518 (\\N{CJK UNIFIED IDEOGRAPH-540E}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 32773 (\\N{CJK UNIFIED IDEOGRAPH-8005}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20351 (\\N{CJK UNIFIED IDEOGRAPH-4F7F}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 29992 (\\N{CJK UNIFIED IDEOGRAPH-7528}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20108 (\\N{CJK UNIFIED IDEOGRAPH-4E8C}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 20301 (\\N{CJK UNIFIED IDEOGRAPH-4F4D}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 22120 (\\N{CJK UNIFIED IDEOGRAPH-5668}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 25105 (\\N{CJK UNIFIED IDEOGRAPH-6211}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 30528 (\\N{CJK UNIFIED IDEOGRAPH-7740}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "/usr/local/lib/python3.10/dist-packages/IPython/core/pylabtools.py:151: UserWarning: Glyph 35273 (\\N{CJK UNIFIED IDEOGRAPH-89C9}) missing from current font.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n",
      "WARNING:matplotlib.font_manager:findfont: Generic family 'sans-serif' not found because none of the following families were found: Kaitt, SimHei\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "plt.scatter(embeddings_openai_2d[:, 0], embeddings_openai_2d[:, 1] , color=color_list )\n",
    "\n",
    "for i in range(len(embeddings_openai_2d)):\n",
    "    plt.text(embeddings_openai_2d[:,0][i], embeddings_openai_2d[:,1][i],  sentences[i] ,color=color_list[i] )\n",
    "\n",
    "# 显示图表\n",
    "plt.show()"
   ]
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